1 Data preparation

1.1 Outline

  • Load scripts: loads libraries and useful scripts used in the analyses; all .R files contained in scripts at the root of the factory are automatically loaded

  • Load data: imports datasets, and may contain some ad hoc changes to the data such as specific data cleaning (not used in other reports), new variables used in the analyses, etc.

1.2 Load packages


library(reportfactory)
library(here)
library(rio) 
library(tidyverse)
library(incidence)
library(distcrete)
library(epitrix)
library(earlyR)
library(projections)
library(linelist)
library(remotes)
library(janitor)
library(kableExtra)
library(DT)
library(cyphr)
library(chngpt)
library(lubridate)
library(ggpubr)
library(ggnewscale)

1.3 Load scripts

These scripts will load:

  • all scripts stored as .R files inside /scripts/
  • all scripts stored as .R files inside /src/

These scripts also contain routines to access the latest clean encrypted data (see next section).


reportfactory::rfh_load_scripts()

1.4 Load clean data

We import the latest NHS pathways data:


x <- import_pathways() %>%
  as_tibble()
x
## # A tibble: 411,954 x 11
##    site_type date       sex   age   ccg_code ccg_name count postcode nhs_region
##    <chr>     <date>     <chr> <chr> <chr>    <chr>    <int> <chr>    <chr>     
##  1 111       2020-03-18 fema… miss… e380000… nhs_glo…     1 gl34fe   South West
##  2 111       2020-03-18 fema… miss… e380001… nhs_sou…     1 ne325nn  North Eas…
##  3 111       2020-03-18 fema… 0-18  e380000… nhs_air…     8 bd57jr   North Eas…
##  4 111       2020-03-18 fema… 0-18  e380000… nhs_ash…     7 tn254ab  South East
##  5 111       2020-03-18 fema… 0-18  e380000… nhs_bar…    35 rm13ae   London    
##  6 111       2020-03-18 fema… 0-18  e380000… nhs_bar…     9 n111np   London    
##  7 111       2020-03-18 fema… 0-18  e380000… nhs_bar…    11 s752py   North Eas…
##  8 111       2020-03-18 fema… 0-18  e380000… nhs_bas…    19 ss143hg  East of E…
##  9 111       2020-03-18 fema… 0-18  e380000… nhs_bas…     6 dn227xf  North Eas…
## 10 111       2020-03-18 fema… 0-18  e380000… nhs_bat…     9 ba25rp   South West
## # … with 411,944 more rows, and 2 more variables: day <int>, weekday <fct>

We also import demographics data for NHS regions in England, used later in our analysis:


path <- here::here("data", "csv", "nhs_region_population_2018.csv")
nhs_region_pop <- rio::import(path) %>%
  mutate(nhs_region = str_to_title(gsub("_"," ",nhs_region)))

nhs_region_pop$nhs_region <- gsub(" Of ", " of ", nhs_region_pop$nhs_region)
nhs_region_pop$nhs_region <- gsub(" And ", " and ", nhs_region_pop$nhs_region)
nhs_region_pop
##                  nhs_region variable      value
## 1                North West     0-18 0.22538599
## 2  North East and Yorkshire     0-18 0.21876449
## 3                  Midlands     0-18 0.22564656
## 4           East of England     0-18 0.22810783
## 5                    London     0-18 0.23764782
## 6                South East     0-18 0.22458811
## 7                South West     0-18 0.20799797
## 8                North West    19-69 0.64274078
## 9  North East and Yorkshire    19-69 0.64437753
## 10                 Midlands    19-69 0.63876675
## 11          East of England    19-69 0.63034229
## 12                   London    19-69 0.67820084
## 13               South East    19-69 0.63267336
## 14               South West    19-69 0.63176131
## 15               North West   70-120 0.13187323
## 16 North East and Yorkshire   70-120 0.13685797
## 17                 Midlands   70-120 0.13558669
## 18          East of England   70-120 0.14154988
## 19                   London   70-120 0.08415135
## 20               South East   70-120 0.14273853
## 21               South West   70-120 0.16024072

Finally, we import publically available deaths per NHS region:


dth <- import_deaths() %>%
  mutate(nhs_region = str_to_title(gsub("_"," ",nhs_region)))

#truncation to account for reporting delay
delay_max <- 21

dth$nhs_region <- gsub(" Of ", " of ", dth$nhs_region)
dth$nhs_region <- gsub(" And ", " and ", dth$nhs_region)
dth
##      date_report               nhs_region deaths
## 1     2020-03-01          East of England      0
## 2     2020-03-02          East of England      1
## 3     2020-03-03          East of England      0
## 4     2020-03-04          East of England      0
## 5     2020-03-05          East of England      0
## 6     2020-03-06          East of England      1
## 7     2020-03-07          East of England      0
## 8     2020-03-08          East of England      0
## 9     2020-03-09          East of England      1
## 10    2020-03-10          East of England      0
## 11    2020-03-11          East of England      0
## 12    2020-03-12          East of England      0
## 13    2020-03-13          East of England      1
## 14    2020-03-14          East of England      2
## 15    2020-03-15          East of England      2
## 16    2020-03-16          East of England      1
## 17    2020-03-17          East of England      1
## 18    2020-03-18          East of England      5
## 19    2020-03-19          East of England      4
## 20    2020-03-20          East of England      2
## 21    2020-03-21          East of England     11
## 22    2020-03-22          East of England     12
## 23    2020-03-23          East of England     11
## 24    2020-03-24          East of England     19
## 25    2020-03-25          East of England     26
## 26    2020-03-26          East of England     36
## 27    2020-03-27          East of England     38
## 28    2020-03-28          East of England     28
## 29    2020-03-29          East of England     43
## 30    2020-03-30          East of England     45
## 31    2020-03-31          East of England     70
## 32    2020-04-01          East of England     62
## 33    2020-04-02          East of England     65
## 34    2020-04-03          East of England     80
## 35    2020-04-04          East of England     71
## 36    2020-04-05          East of England     76
## 37    2020-04-06          East of England     71
## 38    2020-04-07          East of England     93
## 39    2020-04-08          East of England    111
## 40    2020-04-09          East of England     87
## 41    2020-04-10          East of England     74
## 42    2020-04-11          East of England     92
## 43    2020-04-12          East of England    100
## 44    2020-04-13          East of England     78
## 45    2020-04-14          East of England     61
## 46    2020-04-15          East of England     82
## 47    2020-04-16          East of England     74
## 48    2020-04-17          East of England     86
## 49    2020-04-18          East of England     64
## 50    2020-04-19          East of England     67
## 51    2020-04-20          East of England     67
## 52    2020-04-21          East of England     75
## 53    2020-04-22          East of England     67
## 54    2020-04-23          East of England     49
## 55    2020-04-24          East of England     66
## 56    2020-04-25          East of England     54
## 57    2020-04-26          East of England     48
## 58    2020-04-27          East of England     46
## 59    2020-04-28          East of England     58
## 60    2020-04-29          East of England     32
## 61    2020-04-30          East of England     45
## 62    2020-05-01          East of England     49
## 63    2020-05-02          East of England     29
## 64    2020-05-03          East of England     41
## 65    2020-05-04          East of England     19
## 66    2020-05-05          East of England     36
## 67    2020-05-06          East of England     31
## 68    2020-05-07          East of England     33
## 69    2020-05-08          East of England     33
## 70    2020-05-09          East of England     29
## 71    2020-05-10          East of England     22
## 72    2020-05-11          East of England     18
## 73    2020-05-12          East of England     21
## 74    2020-05-13          East of England     27
## 75    2020-05-14          East of England     26
## 76    2020-05-15          East of England     19
## 77    2020-05-16          East of England     26
## 78    2020-05-17          East of England     17
## 79    2020-05-18          East of England     25
## 80    2020-05-19          East of England     15
## 81    2020-05-20          East of England     26
## 82    2020-05-21          East of England     21
## 83    2020-05-22          East of England     13
## 84    2020-05-23          East of England     12
## 85    2020-05-24          East of England     17
## 86    2020-05-25          East of England     25
## 87    2020-05-26          East of England     14
## 88    2020-05-27          East of England     12
## 89    2020-05-28          East of England     17
## 90    2020-05-29          East of England     16
## 91    2020-05-30          East of England      9
## 92    2020-05-31          East of England      8
## 93    2020-06-01          East of England     17
## 94    2020-06-02          East of England     14
## 95    2020-06-03          East of England     10
## 96    2020-06-04          East of England      7
## 97    2020-06-05          East of England     14
## 98    2020-06-06          East of England      5
## 99    2020-06-07          East of England      9
## 100   2020-06-08          East of England      7
## 101   2020-06-09          East of England      6
## 102   2020-06-10          East of England      8
## 103   2020-06-11          East of England      1
## 104   2020-06-12          East of England      9
## 105   2020-06-13          East of England      5
## 106   2020-06-14          East of England      4
## 107   2020-06-15          East of England      8
## 108   2020-06-16          East of England      3
## 109   2020-06-17          East of England      7
## 110   2020-06-18          East of England      4
## 111   2020-06-19          East of England      7
## 112   2020-06-20          East of England      4
## 113   2020-06-21          East of England      3
## 114   2020-06-22          East of England      6
## 115   2020-06-23          East of England      5
## 116   2020-06-24          East of England      4
## 117   2020-06-25          East of England      1
## 118   2020-06-26          East of England      5
## 119   2020-06-27          East of England      6
## 120   2020-06-28          East of England      8
## 121   2020-06-29          East of England      4
## 122   2020-06-30          East of England      5
## 123   2020-07-01          East of England      2
## 124   2020-07-02          East of England      5
## 125   2020-07-03          East of England      0
## 126   2020-07-04          East of England      3
## 127   2020-07-05          East of England      1
## 128   2020-07-06          East of England      2
## 129   2020-07-07          East of England      2
## 130   2020-07-08          East of England      0
## 131   2020-07-09          East of England      8
## 132   2020-07-10          East of England      4
## 133   2020-07-11          East of England      2
## 134   2020-07-12          East of England      1
## 135   2020-07-13          East of England      8
## 136   2020-07-14          East of England      2
## 137   2020-07-15          East of England      0
## 138   2020-07-16          East of England      0
## 139   2020-07-17          East of England      0
## 140   2020-07-18          East of England      0
## 141   2020-07-19          East of England      1
## 142   2020-07-20          East of England      1
## 143   2020-07-21          East of England      1
## 144   2020-07-22          East of England      2
## 145   2020-07-23          East of England      1
## 146   2020-07-24          East of England      1
## 147   2020-07-25          East of England      0
## 148   2020-07-26          East of England      1
## 149   2020-07-27          East of England      1
## 150   2020-07-28          East of England      2
## 151   2020-07-29          East of England      0
## 152   2020-07-30          East of England      0
## 153   2020-07-31          East of England      1
## 154   2020-08-01          East of England      0
## 155   2020-08-02          East of England      0
## 156   2020-08-03          East of England      0
## 157   2020-08-04          East of England      1
## 158   2020-08-05          East of England      1
## 159   2020-08-06          East of England      0
## 160   2020-08-07          East of England      1
## 161   2020-08-08          East of England      0
## 162   2020-08-09          East of England      0
## 163   2020-08-10          East of England      1
## 164   2020-08-11          East of England      2
## 165   2020-08-12          East of England      1
## 166   2020-08-13          East of England      0
## 167   2020-08-14          East of England      1
## 168   2020-08-15          East of England      1
## 169   2020-08-16          East of England      0
## 170   2020-08-17          East of England      0
## 171   2020-08-18          East of England      2
## 172   2020-08-19          East of England      1
## 173   2020-08-20          East of England      1
## 174   2020-08-21          East of England      0
## 175   2020-08-22          East of England      1
## 176   2020-08-23          East of England      1
## 177   2020-08-24          East of England      0
## 178   2020-08-25          East of England      0
## 179   2020-08-26          East of England      1
## 180   2020-08-27          East of England      1
## 181   2020-08-28          East of England      0
## 182   2020-08-29          East of England      0
## 183   2020-08-30          East of England      0
## 184   2020-08-31          East of England      0
## 185   2020-09-01          East of England      0
## 186   2020-09-02          East of England      0
## 187   2020-09-03          East of England      1
## 188   2020-09-04          East of England      1
## 189   2020-09-05          East of England      0
## 190   2020-09-06          East of England      1
## 191   2020-09-07          East of England      0
## 192   2020-09-08          East of England      0
## 193   2020-09-09          East of England      0
## 194   2020-09-10          East of England      0
## 195   2020-09-11          East of England      0
## 196   2020-09-12          East of England      0
## 197   2020-09-13          East of England      1
## 198   2020-09-14          East of England      1
## 199   2020-09-15          East of England      0
## 200   2020-09-16          East of England      0
## 201   2020-09-17          East of England      0
## 202   2020-09-18          East of England      0
## 203   2020-09-19          East of England      0
## 204   2020-09-20          East of England      2
## 205   2020-09-21          East of England      0
## 206   2020-09-22          East of England      2
## 207   2020-09-23          East of England      1
## 208   2020-09-24          East of England      0
## 209   2020-09-25          East of England      1
## 210   2020-09-26          East of England      1
## 211   2020-09-27          East of England      1
## 212   2020-09-28          East of England      2
## 213   2020-09-29          East of England      2
## 214   2020-09-30          East of England      2
## 215   2020-10-01          East of England      2
## 216   2020-10-02          East of England      1
## 217   2020-10-03          East of England      1
## 218   2020-10-04          East of England      0
## 219   2020-10-05          East of England      0
## 220   2020-10-06          East of England      4
## 221   2020-10-07          East of England      6
## 222   2020-10-08          East of England      3
## 223   2020-10-09          East of England      1
## 224   2020-10-10          East of England      6
## 225   2020-10-11          East of England      2
## 226   2020-10-12          East of England      2
## 227   2020-10-13          East of England      1
## 228   2020-10-14          East of England      3
## 229   2020-10-15          East of England      4
## 230   2020-10-16          East of England      5
## 231   2020-10-17          East of England      6
## 232   2020-10-18          East of England      7
## 233   2020-10-19          East of England      5
## 234   2020-10-20          East of England      9
## 235   2020-10-21          East of England      7
## 236   2020-10-22          East of England      7
## 237   2020-10-23          East of England     14
## 238   2020-10-24          East of England      1
## 239   2020-10-25          East of England     10
## 240   2020-10-26          East of England     10
## 241   2020-10-27          East of England      8
## 242   2020-10-28          East of England     12
## 243   2020-10-29          East of England     10
## 244   2020-10-30          East of England     12
## 245   2020-10-31          East of England     15
## 246   2020-11-01          East of England     14
## 247   2020-11-02          East of England      9
## 248   2020-11-03          East of England     14
## 249   2020-11-04          East of England     11
## 250   2020-11-05          East of England     12
## 251   2020-11-06          East of England     18
## 252   2020-11-07          East of England     10
## 253   2020-11-08          East of England     13
## 254   2020-11-09          East of England     16
## 255   2020-11-10          East of England     26
## 256   2020-11-11          East of England     14
## 257   2020-11-12          East of England     14
## 258   2020-11-13          East of England     21
## 259   2020-11-14          East of England     19
## 260   2020-11-15          East of England     13
## 261   2020-11-16          East of England     11
## 262   2020-11-17          East of England     17
## 263   2020-11-18          East of England     19
## 264   2020-11-19          East of England     23
## 265   2020-11-20          East of England     24
## 266   2020-11-21          East of England     19
## 267   2020-11-22          East of England     21
## 268   2020-11-23          East of England     18
## 269   2020-11-24          East of England     21
## 270   2020-11-25          East of England     19
## 271   2020-11-26          East of England     19
## 272   2020-11-27          East of England     14
## 273   2020-11-28          East of England     28
## 274   2020-11-29          East of England     19
## 275   2020-11-30          East of England     22
## 276   2020-12-01          East of England     25
## 277   2020-12-02          East of England     18
## 278   2020-12-03          East of England     23
## 279   2020-12-04          East of England     24
## 280   2020-12-05          East of England     25
## 281   2020-12-06          East of England     21
## 282   2020-12-07          East of England     16
## 283   2020-12-08          East of England     26
## 284   2020-12-09          East of England     19
## 285   2020-12-10          East of England     32
## 286   2020-12-11          East of England     32
## 287   2020-12-12          East of England     27
## 288   2020-12-13          East of England     25
## 289   2020-12-14          East of England     31
## 290   2020-12-15          East of England     35
## 291   2020-12-16          East of England     29
## 292   2020-12-17          East of England     42
## 293   2020-12-18          East of England     44
## 294   2020-12-19          East of England     54
## 295   2020-12-20          East of England     50
## 296   2020-12-21          East of England     64
## 297   2020-12-22          East of England     52
## 298   2020-12-23          East of England     60
## 299   2020-12-24          East of England     54
## 300   2020-12-25          East of England     56
## 301   2020-12-26          East of England     61
## 302   2020-12-27          East of England     53
## 303   2020-12-28          East of England     70
## 304   2020-12-29          East of England     50
## 305   2020-12-30          East of England     69
## 306   2020-12-31          East of England     79
## 307   2021-01-01          East of England     87
## 308   2021-01-02          East of England     65
## 309   2021-01-03          East of England     75
## 310   2021-01-04          East of England     84
## 311   2021-01-05          East of England     99
## 312   2021-01-06          East of England     90
## 313   2021-01-07          East of England    107
## 314   2021-01-08          East of England     82
## 315   2021-01-09          East of England    114
## 316   2021-01-10          East of England    114
## 317   2021-01-11          East of England    119
## 318   2021-01-12          East of England    117
## 319   2021-01-13          East of England    110
## 320   2021-01-14          East of England    100
## 321   2021-01-15          East of England     93
## 322   2021-01-16          East of England    110
## 323   2021-01-17          East of England     96
## 324   2021-01-18          East of England    103
## 325   2021-01-19          East of England     96
## 326   2021-01-20          East of England     82
## 327   2021-01-21          East of England     15
## 328   2020-03-01                   London      0
## 329   2020-03-02                   London      0
## 330   2020-03-03                   London      0
## 331   2020-03-04                   London      0
## 332   2020-03-05                   London      0
## 333   2020-03-06                   London      1
## 334   2020-03-07                   London      0
## 335   2020-03-08                   London      0
## 336   2020-03-09                   London      1
## 337   2020-03-10                   London      0
## 338   2020-03-11                   London      5
## 339   2020-03-12                   London      6
## 340   2020-03-13                   London     10
## 341   2020-03-14                   London     13
## 342   2020-03-15                   London      9
## 343   2020-03-16                   London     15
## 344   2020-03-17                   London     23
## 345   2020-03-18                   London     28
## 346   2020-03-19                   London     25
## 347   2020-03-20                   London     44
## 348   2020-03-21                   London     49
## 349   2020-03-22                   London     54
## 350   2020-03-23                   London     63
## 351   2020-03-24                   London     86
## 352   2020-03-25                   London    112
## 353   2020-03-26                   London    130
## 354   2020-03-27                   London    130
## 355   2020-03-28                   London    123
## 356   2020-03-29                   London    145
## 357   2020-03-30                   London    151
## 358   2020-03-31                   London    183
## 359   2020-04-01                   London    202
## 360   2020-04-02                   London    191
## 361   2020-04-03                   London    199
## 362   2020-04-04                   London    231
## 363   2020-04-05                   London    195
## 364   2020-04-06                   London    198
## 365   2020-04-07                   London    220
## 366   2020-04-08                   London    239
## 367   2020-04-09                   London    207
## 368   2020-04-10                   London    171
## 369   2020-04-11                   London    178
## 370   2020-04-12                   London    159
## 371   2020-04-13                   London    166
## 372   2020-04-14                   London    143
## 373   2020-04-15                   London    143
## 374   2020-04-16                   London    140
## 375   2020-04-17                   London    101
## 376   2020-04-18                   London    101
## 377   2020-04-19                   London    103
## 378   2020-04-20                   London     96
## 379   2020-04-21                   London     96
## 380   2020-04-22                   London    109
## 381   2020-04-23                   London     77
## 382   2020-04-24                   London     71
## 383   2020-04-25                   London     58
## 384   2020-04-26                   London     53
## 385   2020-04-27                   London     52
## 386   2020-04-28                   London     44
## 387   2020-04-29                   London     45
## 388   2020-04-30                   London     40
## 389   2020-05-01                   London     41
## 390   2020-05-02                   London     41
## 391   2020-05-03                   London     36
## 392   2020-05-04                   London     30
## 393   2020-05-05                   London     25
## 394   2020-05-06                   London     37
## 395   2020-05-07                   London     37
## 396   2020-05-08                   London     31
## 397   2020-05-09                   London     23
## 398   2020-05-10                   London     26
## 399   2020-05-11                   London     18
## 400   2020-05-12                   London     18
## 401   2020-05-13                   London     17
## 402   2020-05-14                   London     20
## 403   2020-05-15                   London     19
## 404   2020-05-16                   London     14
## 405   2020-05-17                   London     15
## 406   2020-05-18                   London     11
## 407   2020-05-19                   London     14
## 408   2020-05-20                   London     19
## 409   2020-05-21                   London     12
## 410   2020-05-22                   London     10
## 411   2020-05-23                   London      6
## 412   2020-05-24                   London      7
## 413   2020-05-25                   London      9
## 414   2020-05-26                   London     14
## 415   2020-05-27                   London      7
## 416   2020-05-28                   London      8
## 417   2020-05-29                   London      7
## 418   2020-05-30                   London     12
## 419   2020-05-31                   London      6
## 420   2020-06-01                   London     10
## 421   2020-06-02                   London      8
## 422   2020-06-03                   London      6
## 423   2020-06-04                   London      8
## 424   2020-06-05                   London      4
## 425   2020-06-06                   London      0
## 426   2020-06-07                   London      5
## 427   2020-06-08                   London      5
## 428   2020-06-09                   London      5
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## 966   2021-01-06                 Midlands    109
## 967   2021-01-07                 Midlands    102
## 968   2021-01-08                 Midlands    129
## 969   2021-01-09                 Midlands    137
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## 981   2021-01-21                 Midlands     23
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## 984   2020-03-03 North East and Yorkshire      0
## 985   2020-03-04 North East and Yorkshire      0
## 986   2020-03-05 North East and Yorkshire      0
## 987   2020-03-06 North East and Yorkshire      0
## 988   2020-03-07 North East and Yorkshire      0
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## 996   2020-03-15 North East and Yorkshire      2
## 997   2020-03-16 North East and Yorkshire      3
## 998   2020-03-17 North East and Yorkshire      1
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## 1000  2020-03-19 North East and Yorkshire      6
## 1001  2020-03-20 North East and Yorkshire      5
## 1002  2020-03-21 North East and Yorkshire      6
## 1003  2020-03-22 North East and Yorkshire      7
## 1004  2020-03-23 North East and Yorkshire      9
## 1005  2020-03-24 North East and Yorkshire      8
## 1006  2020-03-25 North East and Yorkshire     18
## 1007  2020-03-26 North East and Yorkshire     21
## 1008  2020-03-27 North East and Yorkshire     28
## 1009  2020-03-28 North East and Yorkshire     35
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## 1011  2020-03-30 North East and Yorkshire     64
## 1012  2020-03-31 North East and Yorkshire     60
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## 1014  2020-04-02 North East and Yorkshire     75
## 1015  2020-04-03 North East and Yorkshire    100
## 1016  2020-04-04 North East and Yorkshire    105
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## 1019  2020-04-07 North East and Yorkshire    102
## 1020  2020-04-08 North East and Yorkshire    107
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## 1026  2020-04-14 North East and Yorkshire    107
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## 1082  2020-06-09 North East and Yorkshire     12
## 1083  2020-06-10 North East and Yorkshire     19
## 1084  2020-06-11 North East and Yorkshire      7
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## 1086  2020-06-13 North East and Yorkshire     10
## 1087  2020-06-14 North East and Yorkshire     11
## 1088  2020-06-15 North East and Yorkshire      9
## 1089  2020-06-16 North East and Yorkshire     10
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## 1091  2020-06-18 North East and Yorkshire     11
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## 1096  2020-06-23 North East and Yorkshire      8
## 1097  2020-06-24 North East and Yorkshire     10
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## 1103  2020-06-30 North East and Yorkshire      7
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## 1106  2020-07-03 North East and Yorkshire      4
## 1107  2020-07-04 North East and Yorkshire      4
## 1108  2020-07-05 North East and Yorkshire      3
## 1109  2020-07-06 North East and Yorkshire      2
## 1110  2020-07-07 North East and Yorkshire      3
## 1111  2020-07-08 North East and Yorkshire      3
## 1112  2020-07-09 North East and Yorkshire      0
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## 1127  2020-07-24 North East and Yorkshire      1
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## 1137  2020-08-03 North East and Yorkshire      1
## 1138  2020-08-04 North East and Yorkshire      3
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## 1142  2020-08-08 North East and Yorkshire      2
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## 1147  2020-08-13 North East and Yorkshire      0
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## 1212  2020-10-17 North East and Yorkshire     34
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## 1219  2020-10-24 North East and Yorkshire     34
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## 1291  2021-01-04 North East and Yorkshire     61
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## 1311  2020-03-03               North West      0
## 1312  2020-03-04               North West      0
## 1313  2020-03-05               North West      1
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## 1319  2020-03-11               North West      0
## 1320  2020-03-12               North West      2
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## 1326  2020-03-18               North West      6
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## 1328  2020-03-20               North West     10
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## 1331  2020-03-23               North West     15
## 1332  2020-03-24               North West     21
## 1333  2020-03-25               North West     21
## 1334  2020-03-26               North West     29
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## 1343  2020-04-04               North West     98
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## 1354  2020-04-15               North West    114
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## 1356  2020-04-17               North West     98
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## 1408  2020-06-08               North West     23
## 1409  2020-06-09               North West     17
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## 1411  2020-06-11               North West     16
## 1412  2020-06-12               North West     11
## 1413  2020-06-13               North West     10
## 1414  2020-06-14               North West     15
## 1415  2020-06-15               North West     16
## 1416  2020-06-16               North West     16
## 1417  2020-06-17               North West     13
## 1418  2020-06-18               North West     14
## 1419  2020-06-19               North West      7
## 1420  2020-06-20               North West     11
## 1421  2020-06-21               North West      8
## 1422  2020-06-22               North West     11
## 1423  2020-06-23               North West     13
## 1424  2020-06-24               North West     13
## 1425  2020-06-25               North West     15
## 1426  2020-06-26               North West      6
## 1427  2020-06-27               North West      7
## 1428  2020-06-28               North West      9
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## 1430  2020-06-30               North West      7
## 1431  2020-07-01               North West      3
## 1432  2020-07-02               North West      6
## 1433  2020-07-03               North West      7
## 1434  2020-07-04               North West      4
## 1435  2020-07-05               North West      6
## 1436  2020-07-06               North West      9
## 1437  2020-07-07               North West      8
## 1438  2020-07-08               North West      5
## 1439  2020-07-09               North West     10
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## 1446  2020-07-16               North West      2
## 1447  2020-07-17               North West      4
## 1448  2020-07-18               North West      5
## 1449  2020-07-19               North West      3
## 1450  2020-07-20               North West      0
## 1451  2020-07-21               North West      2
## 1452  2020-07-22               North West      3
## 1453  2020-07-23               North West      3
## 1454  2020-07-24               North West      1
## 1455  2020-07-25               North West      1
## 1456  2020-07-26               North West      3
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## 1461  2020-07-31               North West      0
## 1462  2020-08-01               North West      2
## 1463  2020-08-02               North West      1
## 1464  2020-08-03               North West      8
## 1465  2020-08-04               North West      3
## 1466  2020-08-05               North West      2
## 1467  2020-08-06               North West      2
## 1468  2020-08-07               North West      2
## 1469  2020-08-08               North West      2
## 1470  2020-08-09               North West      3
## 1471  2020-08-10               North West      2
## 1472  2020-08-11               North West      3
## 1473  2020-08-12               North West      0
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## 1477  2020-08-16               North West      2
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## 1482  2020-08-21               North West      4
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## 1484  2020-08-23               North West      5
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## 1493  2020-09-01               North West      0
## 1494  2020-09-02               North West      2
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## 1496  2020-09-04               North West      3
## 1497  2020-09-05               North West      6
## 1498  2020-09-06               North West      1
## 1499  2020-09-07               North West      8
## 1500  2020-09-08               North West      6
## 1501  2020-09-09               North West      5
## 1502  2020-09-10               North West      5
## 1503  2020-09-11               North West      1
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## 1524  2020-10-02               North West     20
## 1525  2020-10-03               North West     15
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## 1556  2020-11-03               North West     76
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## 1964  2020-03-02               South West      0
## 1965  2020-03-03               South West      0
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## 2007  2020-04-14               South West     24
## 2008  2020-04-15               South West     32
## 2009  2020-04-16               South West     29
## 2010  2020-04-17               South West     33
## 2011  2020-04-18               South West     25
## 2012  2020-04-19               South West     31
## 2013  2020-04-20               South West     26
## 2014  2020-04-21               South West     26
## 2015  2020-04-22               South West     23
## 2016  2020-04-23               South West     17
## 2017  2020-04-24               South West     19
## 2018  2020-04-25               South West     15
## 2019  2020-04-26               South West     27
## 2020  2020-04-27               South West     13
## 2021  2020-04-28               South West     17
## 2022  2020-04-29               South West     15
## 2023  2020-04-30               South West     26
## 2024  2020-05-01               South West      6
## 2025  2020-05-02               South West      7
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## 2078  2020-06-24               South West      1
## 2079  2020-06-25               South West      0
## 2080  2020-06-26               South West      3
## 2081  2020-06-27               South West      0
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## 2083  2020-06-29               South West      1
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## 2088  2020-07-04               South West      0
## 2089  2020-07-05               South West      1
## 2090  2020-07-06               South West      0
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## 2092  2020-07-08               South West      2
## 2093  2020-07-09               South West      0
## 2094  2020-07-10               South West      1
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## 2097  2020-07-13               South West      1
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## 2099  2020-07-15               South West      0
## 2100  2020-07-16               South West      0
## 2101  2020-07-17               South West      1
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## 2112  2020-07-28               South West      0
## 2113  2020-07-29               South West      0
## 2114  2020-07-30               South West      1
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## 2127  2020-08-12               South West      0
## 2128  2020-08-13               South West      0
## 2129  2020-08-14               South West      1
## 2130  2020-08-15               South West      0
## 2131  2020-08-16               South West      0
## 2132  2020-08-17               South West      2
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## 2139  2020-08-24               South West      0
## 2140  2020-08-25               South West      1
## 2141  2020-08-26               South West      0
## 2142  2020-08-27               South West      1
## 2143  2020-08-28               South West      0
## 2144  2020-08-29               South West      0
## 2145  2020-08-30               South West      0
## 2146  2020-08-31               South West      0
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## 2154  2020-09-08               South West      1
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## 2158  2020-09-12               South West      0
## 2159  2020-09-13               South West      1
## 2160  2020-09-14               South West      0
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## 2163  2020-09-17               South West      1
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## 2166  2020-09-20               South West      1
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## 2169  2020-09-23               South West      0
## 2170  2020-09-24               South West      1
## 2171  2020-09-25               South West      0
## 2172  2020-09-26               South West      0
## 2173  2020-09-27               South West      0
## 2174  2020-09-28               South West      0
## 2175  2020-09-29               South West      0
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## 2178  2020-10-02               South West      1
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## 2182  2020-10-06               South West      1
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## 2186  2020-10-10               South West      0
## 2187  2020-10-11               South West      4
## 2188  2020-10-12               South West      2
## 2189  2020-10-13               South West      0
## 2190  2020-10-14               South West      3
## 2191  2020-10-15               South West      1
## 2192  2020-10-16               South West      2
## 2193  2020-10-17               South West      8
## 2194  2020-10-18               South West      2
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## 2196  2020-10-20               South West      3
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## 2201  2020-10-25               South West      5
## 2202  2020-10-26               South West      7
## 2203  2020-10-27               South West      6
## 2204  2020-10-28               South West      8
## 2205  2020-10-29               South West     11
## 2206  2020-10-30               South West      8
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## 2208  2020-11-01               South West      5
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## 2224  2020-11-17               South West     17
## 2225  2020-11-18               South West     26
## 2226  2020-11-19               South West     15
## 2227  2020-11-20               South West     25
## 2228  2020-11-21               South West     25
## 2229  2020-11-22               South West     23
## 2230  2020-11-23               South West     14
## 2231  2020-11-24               South West     20
## 2232  2020-11-25               South West     25
## 2233  2020-11-26               South West     16
## 2234  2020-11-27               South West     21
## 2235  2020-11-28               South West     35
## 2236  2020-11-29               South West     15
## 2237  2020-11-30               South West     21
## 2238  2020-12-01               South West     19
## 2239  2020-12-02               South West     15
## 2240  2020-12-03               South West     14
## 2241  2020-12-04               South West     20
## 2242  2020-12-05               South West     17
## 2243  2020-12-06               South West     13
## 2244  2020-12-07               South West     14
## 2245  2020-12-08               South West     19
## 2246  2020-12-09               South West     21
## 2247  2020-12-10               South West     20
## 2248  2020-12-11               South West     20
## 2249  2020-12-12               South West     15
## 2250  2020-12-13               South West     19
## 2251  2020-12-14               South West     20
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## 2253  2020-12-16               South West      9
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## 2257  2020-12-20               South West     19
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## 2259  2020-12-22               South West     10
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## 2261  2020-12-24               South West     18
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## 2263  2020-12-26               South West     24
## 2264  2020-12-27               South West     24
## 2265  2020-12-28               South West     20
## 2266  2020-12-29               South West     20
## 2267  2020-12-30               South West     14
## 2268  2020-12-31               South West     26
## 2269  2021-01-01               South West     28
## 2270  2021-01-02               South West     22
## 2271  2021-01-03               South West     24
## 2272  2021-01-04               South West     30
## 2273  2021-01-05               South West     30
## 2274  2021-01-06               South West     24
## 2275  2021-01-07               South West     29
## 2276  2021-01-08               South West     33
## 2277  2021-01-09               South West     26
## 2278  2021-01-10               South West     31
## 2279  2021-01-11               South West     35
## 2280  2021-01-12               South West     48
## 2281  2021-01-13               South West     40
## 2282  2021-01-14               South West     32
## 2283  2021-01-15               South West     43
## 2284  2021-01-16               South West     54
## 2285  2021-01-17               South West     30
## 2286  2021-01-18               South West     41
## 2287  2021-01-19               South West     34
## 2288  2021-01-20               South West     38
## 2289  2021-01-21               South West      8

1.5 Completion date

We extract the completion date from the NHS Pathways file timestamp:


database_date <- attr(x, "timestamp")
database_date
## [1] "2021-01-21"

The completion date of the NHS Pathways data is Thursday 21 Jan 2021.

1.6 Auxiliary functions

These are functions which will be used further in the analyses.

Function to estimate the generalised R-squared as the proportion of deviance explained by a given model:


## Function to calculate R2 for Poisson model
## not adjusted for model complexity but all models have the same DF here

Rsq <- function(x) {
  1 - (x$deviance / x$null.deviance)
}

Function to extract growth rates per region as well as halving times, and the associated 95% confidence intervals:


## function to extract the coefficients, find the level of the intercept,
## reconstruct the values of r, get confidence intervals

get_r <- function(model) {
  ##  extract coefficients and conf int
  out <- data.frame(r = coef(model))  %>%
    rownames_to_column("var") %>% 
    cbind(confint(model)) %>%
    filter(!grepl("day_of_week", var)) %>% 
    filter(grepl("day", var)) %>%
    rename(lower_95 = "2.5 %",
           upper_95 = "97.5 %") %>%
    mutate(var = sub("day:", "", var))
  
  ## reconstruct values: intercept + region-coefficient
  for (i in 2:nrow(out)) {
    out[i, -1] <- out[1, -1] + out[i, -1]
  }
  
  ## find the name of the intercept, restore regions names
  out <- out %>%
    mutate(nhs_region = model$xlevels$nhs_region) %>%
    select(nhs_region, everything(), -var)
  
  ## find halving times
  halving <- log(0.5) / out[,-1] %>%
    rename(halving_t = r,
           halving_t_lower_95 = lower_95,
           halving_t_upper_95 = upper_95)
  
  ## set halving times with exclusion intervals to NA
  no_halving <- out$lower_95 < 0 & out$upper_95 > 0
  halving[no_halving, ] <- NA_real_
  
  ## return all data
  cbind(out, halving)
  
}

Functions used in the correlation analysis between NHS Pathways reports and deaths:

## Function to calculate Pearson's correlation between deaths and lagged
## reports. Note that `pearson` can be replaced with `spearman` for rank
## correlation.

getcor <- function(x, ndx) {
  return(cor(x$deaths[ndx],
             x$note_lag[ndx],
             use = "complete.obs",
             method = "pearson"))
}

## Catch if sample size throws an error
getcor2 <- possibly(getcor, otherwise = NA)

getboot <- function(x) {
  result <- boot::boot.ci(boot::boot(x, getcor2, R = 1000), 
                           type = "bca")
  return(data.frame(n = sum(!is.na(x$note_lag) & !is.na(x$deaths)),
                    r = result$t0,
                    r_low = result$bca[4],
                    r_hi = result$bca[5]))
}

Function to classify the day of the week into weekend, Monday, and the rest:


## Fn to add day of week
day_of_week <- function(df) {
  df %>% 
    dplyr::mutate(day_of_week = lubridate::wday(date, label = TRUE)) %>% 
    dplyr::mutate(day_of_week = dplyr::case_when(
      day_of_week %in% c("Sat", "Sun") ~ "weekend",
      day_of_week %in% c("Mon") ~ "monday",
      !(day_of_week %in% c("Sat", "Sun", "Mon")) ~ "rest_of_week"
    ) %>% 
      factor(levels = c("rest_of_week", "monday", "weekend")))
}

Custom color palettes, color scales, and vectors of colors:


pal <- c("#006212",
         "#ae3cab",
         "#00db90",
         "#960c00",
         "#55aaff",
         "#ff7e78",
         "#00388d")

age.pal <- viridis::viridis(3,begin = 0.1, end = 0.7)

3 Comparison with deaths time series

3.1 Outline

We want to explore the correlation between NHS Pathways reports and deaths, and assess the potential for reports to be used as an early warning system for disease resurgence.

Death data are publically available. We truncate the time series to avoid bias from reporting delay - we assume a conservative delay of three weeks.

3.2 Lagged correlation

We calculate Pearson’s correlation coefficient between deaths and NHS Pathways notifications using different lags. Confidence intervals are obtained using bootstrap. Note that results were also confirmed using Spearman’s rank correlation.

First we join the NHS Pathways and death data, and aggregate over all England:

## truncate death data for reporting delay
trunc_date <- max(dth$date_report) - delay_max

dth_trunc <- dth %>%
  rename(date = date_report) %>%
  filter(date <= trunc_date) 

## join with notification data
all_data <- x %>% 
  filter(!is.na(nhs_region)) %>%
  group_by(date, nhs_region) %>%
  summarise(count = sum(count, na.rm = T)) %>%
  ungroup %>%
  inner_join(dth_trunc,
             by = c("date","nhs_region"))

all_tot <- all_data %>%
  group_by(date) %>%
  summarise(count = sum(count, na.rm = TRUE),
            deaths = sum(deaths, na.rm = TRUE)) 

We calculate correlation with lagged NHS Pathways reports from 0 to 30 days behind deaths:


## Calculate all correlations + bootstrap CIs
lag_cor <- data.frame()
for (i in 0:30) {
  
  ## lag reports
  summary <- all_tot %>% 
    mutate(note_lag = lag(count, i)) %>%
    ## calculate rank correlation and bootstrap CI
    getboot(.) %>%
    mutate(lag = i)

  lag_cor <- bind_rows(lag_cor, summary)
}

cor_vs_lag <- ggplot(lag_cor, aes(lag, r)) +
  theme_bw() +
  geom_ribbon(aes(ymin = r_low, ymax = r_hi), alpha = 0.2) +
  geom_hline(yintercept = 0, lty = "longdash") +
  geom_point() +
  geom_line() +
  labs(x = "Lag between NHS pathways and death data (days)",
       y = "Pearson's correlation") +
  large_txt
cor_vs_lag


l_opt <- which.max(lag_cor$r)

This analysis suggests that the best lag is 16 days. We then compare and plot the number of deaths reported against the number of NHS Pathways reports lagged by 16 days.


all_tot <- all_tot %>%
  rename(date_death = date) %>%
  mutate(note_lag = lag(count, lag_cor$lag[l_opt]),
         note_lag_c = (note_lag - mean(note_lag, na.rm = T)),
         date_note = lag(date_death,16))

lag_mod <- glm(deaths ~ note_lag, data = all_tot, family = "quasipoisson")

summary(lag_mod)
## 
## Call:
## glm(formula = deaths ~ note_lag, family = "quasipoisson", data = all_tot)
## 
## Deviance Residuals: 
##     Min       1Q   Median       3Q      Max  
## -14.842  -12.350   -4.742    8.146   24.678  
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 4.729e+00  6.443e-02   73.40   <2e-16 ***
## note_lag    1.518e-05  9.622e-07   15.78   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for quasipoisson family taken to be 117.5311)
## 
##     Null deviance: 53767  on 272  degrees of freedom
## Residual deviance: 32867  on 271  degrees of freedom
##   (16 observations deleted due to missingness)
## AIC: NA
## 
## Number of Fisher Scoring iterations: 5

exp(coefficients(lag_mod))
## (Intercept)    note_lag 
##  113.228185    1.000015
exp(confint(lag_mod))
##                 2.5 %     97.5 %
## (Intercept) 99.564953 128.182898
## note_lag     1.000013   1.000017

Rsq(lag_mod)
## [1] 0.388704

mod_fit <- as.data.frame(predict(lag_mod, type = "link", se.fit = TRUE)[1:2])

all_tot_pred <- 
  all_tot %>%
  filter(!is.na(note_lag)) %>%
  mutate(pred = mod_fit$fit,
         pred.se = mod_fit$se.fit,
         low = exp(pred - 1.96*pred.se),
         hi = exp(pred + 1.96*pred.se))


glm_fit <- all_tot_pred %>% 
    filter(!is.na(note_lag)) %>%
  ggplot(aes(x = note_lag, y = deaths)) +
  geom_point() + 
  geom_line(aes(y = exp(pred))) + 
  geom_ribbon(aes(ymin = low, ymax = hi), alpha = 0.3, col = "grey") +
  theme_bw() +
  labs(y = "Daily number of\ndeaths reported",
       x = "Daily number of NHS Pathways reports") +
  large_txt

glm_fit

4 Supplementary figures

4.1 Serial interval distribution

This is a comparison of gamma versus lognormal distribution for the serial interval used to convert r to R in our analysis. Both distributions are parameterised with mean 4.7 and standard deviation 2.9.

SI_param <- epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
                                        shape = SI_param$shape,
                                        scale = SI_param$scale, w = 0.5)

SI_distribution2 <- distcrete::distcrete("lnorm", interval = 1,
                                        meanlog = log(4.7),
                                        sdlog = log(2.9), w = 0.5)

SI_dist1 <- data.frame(x = SI_distribution$r(1e5)) 
SI_dist1 <- count(SI_dist1, x) %>%
    ggplot() +
    geom_col(aes(x = x, y = n)) +
    labs(x = "Serial interval (days)", y = "Frequency") +
    scale_x_continuous(breaks = seq(0, 30, 5)) +
    theme_bw()

SI_dist2 <- data.frame(x = SI_distribution2$r(1e5)) 
SI_dist2 <- count(SI_dist2, x) %>%
    ggplot() +
    geom_col(aes(x = x, y = n)) +
    labs(x = "Serial interval (days)", y = "Frequency") +
    scale_x_continuous(breaks = seq(0, 200, 20), limits = c(0, 200)) +
    theme_bw()


ggpubr::ggarrange(SI_dist1,
                  SI_dist2,
                  nrow = 1,
                  labels = "AUTO") 

4.2 Sensitivity analysis - 7 or 21 days moving window

We reproduce the window analysis with either a 7 or 21 days window for sensitivity purposes.

First with the 7 days window:

## set moving time window (1/2/3 weeks)
w <- 7

# create empty df
r_all_sliding_7days <- NULL

## make data for model
x_model_all_moving <- x %>%
  filter(!is.na(nhs_region)) %>% 
  group_by(date, nhs_region) %>%
  summarise(n = sum(count)) 

unique_dates <- unique(x_model_all_moving$date)

for (i in 1:(length(unique_dates) - w)) {
  
  date_i <- unique_dates[i]
  
  date_i_max <- date_i + w
  
  model_data <- x_model_all_moving %>%
    filter(date >= date_i & date < date_i_max) %>%
    mutate(day = as.integer(date - date_i)) %>% 
    day_of_week()
  
  
  mod <- glm(n ~ day * nhs_region + day_of_week,
             data = model_data,
             family = 'quasipoisson')
  
  # get growth rate
  r <- get_r(mod)
  r$w_min <- date_i
  r$w_max <- date_i_max
  
  # combine all estimates
  r_all_sliding_7days <- bind_rows(r_all_sliding_7days, r)
  
}

#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
                                        shape = SI_param$shape,
                                        scale = SI_param$scale,
                                        w = 0.5)

#convert growth rates r to R0
r_all_sliding_7days <- r_all_sliding_7days %>%
  mutate(R = epitrix::r2R0(r, SI_distribution),
         R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
         R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))
# plot
plot_growth <-
  r_all_sliding_7days %>%
  ggplot(aes(x = w_max, y = r)) +
  geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
  geom_line(aes(colour = nhs_region)) +
  geom_point(aes(colour = nhs_region)) +
  geom_hline(yintercept = 0, linetype = "dashed") +
  theme_bw() +
  scale_weeks +
  theme(legend.position = "bottom",
        plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
  guides(colour = guide_legend(title = "",override.aes = list(fill = NA)), fill = FALSE) +
  labs(x = "",
       y = "Estimated daily growth rate (r)") +
  scale_colour_manual(values = pal)
plot_R <- r_all_sliding_7days %>%
  ggplot(aes(x = w_max, y = R)) +
  geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
  geom_line(aes(colour = nhs_region)) +
  geom_point(aes(colour = nhs_region)) +
  geom_hline(yintercept = 1, linetype = "dashed") +
  theme_bw() +
  scale_weeks +
  theme(legend.position = "bottom",
        plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
  guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
  labs(x = "",
       y = "Estimated effective reproduction\nnumber (Re)") +
  scale_colour_manual(values = pal)

R <- r_all_sliding_7days %>%
  mutate(lower_95 = R_lower_95, 
         upper_95 = R_upper_95,
         value = R,
         measure = "R",
         reference = 1)

r_R <- r_all_sliding_7days %>%
  mutate(measure = "r",
         value = r,
         reference = 0) %>%
  bind_rows(R)

r_R_7 <- r_R %>%
  ggplot(aes(x = w_max, y = value)) +
  geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
  geom_line(aes(colour = nhs_region)) +
  geom_point(aes(colour = nhs_region)) +
  geom_hline(aes(yintercept = reference), linetype = "dashed") +
  theme_bw() +
  scale_weeks +
  theme(legend.position = "bottom",
        plot.margin = margin(0.5,1,0,0, "cm"),
        strip.background = element_blank(),
        strip.placement = "outside"
  ) +
  guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
  labs(x = "", y = "") +
  scale_colour_manual(values = pal) +
  facet_grid(rows = vars(measure),
             scales = "free_y",
             switch = "y",
             labeller = as_labeller(c(r = "Daily growth rate (r)",
                                      R = "Effective reproduction\nnumber (Re)")))

Then with the 21 days window:

## set moving time window (1/2/3 weeks)
w <- 21

# create empty df
r_all_sliding_21days <- NULL

## make data for model
x_model_all_moving <- x %>%
  filter(!is.na(nhs_region)) %>% 
  group_by(date, nhs_region) %>%
  summarise(n = sum(count)) 

unique_dates <- unique(x_model_all_moving$date)

for (i in 1:(length(unique_dates) - w)) {
  
  date_i <- unique_dates[i]
  
  date_i_max <- date_i + w
  
  model_data <- x_model_all_moving %>%
    filter(date >= date_i & date < date_i_max) %>%
    mutate(day = as.integer(date - date_i)) %>% 
    day_of_week()
  
  
  mod <- glm(n ~ day * nhs_region + day_of_week,
             data = model_data,
             family = 'quasipoisson')
  
  # get growth rate
  r <- get_r(mod)
  r$w_min <- date_i
  r$w_max <- date_i_max
  
  # combine all estimates
  r_all_sliding_21days <- bind_rows(r_all_sliding_21days, r)
  
}

#serial interval distribution
SI_param = epitrix::gamma_mucv2shapescale(4.7, 2.9/4.7)
SI_distribution <- distcrete::distcrete("gamma", interval = 1,
                                        shape = SI_param$shape,
                                        scale = SI_param$scale,
                                        w = 0.5)

#convert growth rates r to R0
r_all_sliding_21days <- r_all_sliding_21days %>%
  mutate(R = epitrix::r2R0(r, SI_distribution),
         R_lower_95 = epitrix::r2R0(lower_95, SI_distribution),
         R_upper_95 = epitrix::r2R0(upper_95, SI_distribution))
# plot
plot_growth <-
  r_all_sliding_21days %>%
  ggplot(aes(x = w_max, y = r)) +
  geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
  geom_line(aes(colour = nhs_region)) +
  geom_point(aes(colour = nhs_region)) +
  geom_hline(yintercept = 0, linetype = "dashed") +
  theme_bw() +
  scale_weeks +
  theme(legend.position = "bottom",
        plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
  guides(colour = guide_legend(title = "",override.aes = list(fill = NA)), fill = FALSE) +
  labs(x = "",
       y = "Estimated daily growth rate (r)") +
  scale_colour_manual(values = pal)
# plot
plot_R <-
  r_all_sliding_21days %>%
  ggplot(aes(x = w_max, y = R)) +
  geom_ribbon(aes(ymin = R_lower_95, ymax = R_upper_95, fill = nhs_region), alpha = 0.1) +
  geom_line(aes(colour = nhs_region)) +
  geom_point(aes(colour = nhs_region)) +
  geom_hline(yintercept = 1, linetype = "dashed") +
  theme_bw() +
  scale_weeks +
  theme(legend.position = "bottom",
        plot.margin = margin(0.5,1,0.5,0.5, "cm")) +
  guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
  labs(x = "",
       y = "Estimated effective reproduction\nnumber (Re)") +
  scale_colour_manual(values = pal)

R <- r_all_sliding_21days %>%
  mutate(lower_95 = R_lower_95, 
         upper_95 = R_upper_95,
         value = R,
         measure = "R",
         reference = 1)

r_R <- r_all_sliding_21days %>%
  mutate(measure = "r",
         value = r,
         reference = 0) %>%
  bind_rows(R)

r_R_21 <- r_R %>%
  ggplot(aes(x = w_max, y = value)) +
  geom_ribbon(aes(ymin = lower_95, ymax = upper_95, fill = nhs_region), alpha = 0.1) +
  geom_line(aes(colour = nhs_region)) +
  geom_point(aes(colour = nhs_region)) +
  geom_hline(aes(yintercept = reference), linetype = "dashed") +
  theme_bw() +
  scale_weeks +
  theme(legend.position = "bottom",
        plot.margin = margin(0.5,1,0,0, "cm"),
        strip.background = element_blank(),
        strip.placement = "outside"
  ) +
  guides(color = guide_legend(title = "", override.aes = list(fill = NA)), fill = FALSE) +
  labs(x = "", y = "") +
  scale_colour_manual(values = pal) +
  facet_grid(rows = vars(measure),
             scales = "free_y",
             switch = "y",
             labeller = as_labeller(c(r = "Daily growth rate (r)",
                                      R = "Effective reproduction\nnumber (Re)")))

And we combine both outputs into a single plot:


ggpubr::ggarrange(r_R_7,
                  r_R_21,
                  nrow = 2,
                  labels = "AUTO",
                  common.legend = TRUE,
                  legend = "bottom") 

4.3 Correlation between NHS Pathways reports and deaths by NHS region


lag_cor_reg <- data.frame()

for (i in 0:30) {

  summary <-
    all_data %>%
    group_by(nhs_region) %>%
    mutate(note_lag = lag(count, i)) %>%
    ## calculate rank correlation and bootstrap CI for each region
    group_modify(~getboot(.x)) %>%
    mutate(lag = i)
  
  lag_cor_reg <- bind_rows(lag_cor_reg, summary)
}

cor_vs_lag_reg <- 
lag_cor_reg %>%
ggplot(aes(lag, r, col = nhs_region)) +
  geom_hline(yintercept = 0, lty = "longdash") +
  geom_ribbon(aes(ymin = r_low, ymax = r_hi, col = NULL, fill = nhs_region), alpha = 0.2) +
  geom_point() +
  geom_line() +
  facet_wrap(~nhs_region) +
  scale_color_manual(values = pal) +
  scale_fill_manual(values = pal, guide = F) +  
  theme_bw() +
  labs(x = "Lag between NHS pathways and death data (days)", y = "Pearson's correlation", col = "NHS region") +
  theme(legend.position = "bottom") +
  guides(color = guide_legend(override.aes = list(fill = NA)))

cor_vs_lag_reg

5 Export data

We save the tables created during our analysis:


if (!dir.exists("excel_tables")) {
  dir.create("excel_tables")
}


## list all tables, and loop over export
tables_to_export <- c("r_all_sliding", "lag_cor")

for (e in tables_to_export) {
  rio::export(get(e),
              file.path("excel_tables",
                        paste0(e, ".xlsx")))
}

## also export result from regression on lagged data 
rio::export(lag_mod, file.path("excel_tables", "lag_mod.rds"))

6 System information

6.1 Outline

The following information documents the system on which the document was compiled.

6.2 System

This provides information on the operating system.

Sys.info()
##                                                                                              sysname 
##                                                                                             "Darwin" 
##                                                                                              release 
##                                                                                             "19.6.0" 
##                                                                                              version 
## "Darwin Kernel Version 19.6.0: Thu Oct 29 22:56:45 PDT 2020; root:xnu-6153.141.2.2~1/RELEASE_X86_64" 
##                                                                                             nodename 
##                                                                            "Mac-1611398302705.local" 
##                                                                                              machine 
##                                                                                             "x86_64" 
##                                                                                                login 
##                                                                                               "root" 
##                                                                                                 user 
##                                                                                             "runner" 
##                                                                                       effective_user 
##                                                                                             "runner"

6.3 R environment

This provides information on the version of R used:

R.version
##                _                           
## platform       x86_64-apple-darwin17.0     
## arch           x86_64                      
## os             darwin17.0                  
## system         x86_64, darwin17.0          
## status                                     
## major          4                           
## minor          0.3                         
## year           2020                        
## month          10                          
## day            10                          
## svn rev        79318                       
## language       R                           
## version.string R version 4.0.3 (2020-10-10)
## nickname       Bunny-Wunnies Freak Out

6.4 R packages

This provides information on the packages used:

sessionInfo()
## R version 4.0.3 (2020-10-10)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Catalina 10.15.7
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
## 
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
##  [1] ggnewscale_0.4.5     ggpubr_0.4.0         lubridate_1.7.9.2   
##  [4] chngpt_2020.10-12    cyphr_1.1.0          DT_0.17             
##  [7] kableExtra_1.3.1     janitor_2.1.0        remotes_2.2.0       
## [10] projections_0.5.2    earlyR_0.0.5         epitrix_0.2.2       
## [13] distcrete_1.0.3      incidence_1.7.3      rio_0.5.16          
## [16] reshape2_1.4.4       rvest_0.3.6          xml2_1.3.2          
## [19] linelist_0.0.40.9000 forcats_0.5.0        stringr_1.4.0       
## [22] dplyr_1.0.3          purrr_0.3.4          readr_1.4.0         
## [25] tidyr_1.1.2          tibble_3.0.5         ggplot2_3.3.3       
## [28] tidyverse_1.3.0      here_1.0.1           reportfactory_0.0.5 
## 
## loaded via a namespace (and not attached):
##  [1] minqa_1.2.4       colorspace_2.0-0  selectr_0.4-2     ggsignif_0.6.0   
##  [5] ellipsis_0.3.1    rprojroot_2.0.2   snakecase_0.11.0  fs_1.5.0         
##  [9] rstudioapi_0.13   farver_2.0.3      fansi_0.4.2       splines_4.0.3    
## [13] knitr_1.30        jsonlite_1.7.2    nloptr_1.2.2.2    broom_0.7.3      
## [17] dbplyr_2.0.0      compiler_4.0.3    httr_1.4.2        backports_1.2.1  
## [21] assertthat_0.2.1  Matrix_1.2-18     cli_2.2.0         htmltools_0.5.1.1
## [25] tools_4.0.3       gtable_0.3.0      glue_1.4.2        Rcpp_1.0.6       
## [29] carData_3.0-4     cellranger_1.1.0  vctrs_0.3.6       nlme_3.1-149     
## [33] matchmaker_0.1.1  crosstalk_1.1.1   xfun_0.20         ps_1.5.0         
## [37] openxlsx_4.2.3    lme4_1.1-26       lifecycle_0.2.0   statmod_1.4.35   
## [41] rstatix_0.6.0     MASS_7.3-53       scales_1.1.1      hms_1.0.0        
## [45] parallel_4.0.3    sodium_1.1        yaml_2.2.1        curl_4.3         
## [49] gridExtra_2.3     stringi_1.5.3     kyotil_2020.10-12 boot_1.3-25      
## [53] zip_2.1.1         rlang_0.4.10      pkgconfig_2.0.3   evaluate_0.14    
## [57] lattice_0.20-41   labeling_0.4.2    htmlwidgets_1.5.3 cowplot_1.1.1    
## [61] tidyselect_1.1.0  plyr_1.8.6        magrittr_2.0.1    R6_2.5.0         
## [65] generics_0.1.0    DBI_1.1.1         pillar_1.4.7      haven_2.3.1      
## [69] foreign_0.8-80    withr_2.4.0       mgcv_1.8-33       survival_3.2-7   
## [73] abind_1.4-5       modelr_0.1.8      crayon_1.3.4      car_3.0-10       
## [77] utf8_1.1.4        rmarkdown_2.6     viridis_0.5.1     grid_4.0.3       
## [81] readxl_1.3.1      data.table_1.13.6 reprex_0.3.0      digest_0.6.27    
## [85] webshot_0.5.2     munsell_0.5.0     viridisLite_0.3.0